{"id":"W4391559823","doi":"10.1016/j.envint.2024.108473","title":"Constraining East Asia ammonia emissions through satellite observations and iterative Finite Difference Mass Balance (iFDMB) and investigating its impact on inorganic fine particulate matter","year":2024,"lang":"en","type":"article","venue":"Environment International","topic":"Atmospheric chemistry and aerosols","field":"Earth and Planetary Sciences","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"Environment and Climate Change Canada","funders":"","keywords":"Particulates; Environmental science; Sulfate; Nitrate; East Asia; Mass concentration (chemistry); Atmospheric sciences; Ammonia; Environmental chemistry; Ammonium sulfate; Sulfur; Ammonium; Relative humidity; China; Meteorology; Chemistry; Geography; Physics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.00007363817,0.0001579836,0.000103952,0.000006588883,0.0001248138,0.0001661539,0.00008251968,0.00004396649,0.003908293],"category_scores_gemma":[0.00003878704,0.000121825,0.00002744541,0.00005341017,0.0001226191,0.0002382793,0.00002304751,0.0001718179,0.0001022816],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001671877,"about_ca_system_score_gemma":0.00002077135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001501808,"about_ca_topic_score_gemma":0.000003298924,"domain_scores_codex":[0.9991256,0.00002606605,0.0001828604,0.0002917724,0.0002138597,0.0001598134],"domain_scores_gemma":[0.99955,0.0002148248,0.00005293132,0.00007427434,0.000007462474,0.000100528],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001024947,0.00001259005,0.9762678,0.00001987395,0.00006532935,0.00001999386,0.001104271,0.003870919,0.01621236,0.0001619475,0.0000981648,0.002156554],"study_design_scores_gemma":[0.0001558151,0.00004191086,0.9260063,0.0002114564,0.00001314468,0.00002308185,0.0001100244,0.06932931,0.001819876,0.0006209358,0.001492135,0.0001760165],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9948034,0.0004979614,0.0004964936,0.001828885,0.00009621646,0.0000794725,0.0003885125,0.00002399986,0.001785022],"genre_scores_gemma":[0.9960178,0.0001501821,0.002174559,0.00019802,0.00008006817,0.000003271953,0.0002363271,0.000004783911,0.001134949],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06545839,"threshold_uncertainty_score":0.9970022,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0271920273086025,"score_gpt":0.2391893871985152,"score_spread":0.2119973598899127,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}